NCT00001174 Starting in 1993, in collaboration with 10 academic centers across the US, we recruited a large sample of over 3,000 individuals with bipolar or other mood disorders. All participants did a diagnostic interview and provided a blood sample for DNA analysis. DNA and clinical data are available through the NIMH Center for Genetics. Genetic linkage studies suggested several chromosomal regions may contain genes that contribute to mood disorders in this sample. To identify individual causal genes, we conducted the first genome-wide association study (GWAS) of bipolar disorder (BD) in 2007. The results implicated several genes, each of small effect, suggesting that BD is a polygenic disease. A second, larger study published in 2010 implicated a cluster of genes on chromosome 3p21 and suggested genetic overlap with major depression. An even larger study published in 2013 that included patients of Asian ancestry supported many of the previous findings and found 3 additional genetic markers of BD. Most of these findings have now been replicated in independent samples. To identify additional risk loci, this year we performed a meta-analysis of >9 million genetic variants in over 40,000 individuals, the largest GWAS of BD to date. To increase power, we used 2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to 4 known loci, we identified 2 novel loci. Our results added to a growing list of common variants involved in BD. To identify rarer genetic variants that may have a larger impact on risk for major mood disorders, we have undertaken genome sequencing studies in families and special populations. So far, we have collected more than 700 individuals from Amish and Mennonite communities whose unique genetic history makes them especially good candidates for this kind of study. All blood samples are processed by the Rutgers Cell and DNA Repository, which also establishes lymphoblastoid cell lines and distributes DNA as a resource for the general scientific community. Last year we added additional measures of neurocognition to our assessments. These data will allow us to better characterize the range of phenotypes present in carriers of risk alleles, many of whom are not expected to have diagnosable mental illness. Through a collaboration with investigators at the Univ of Maryland, we will also investigate brain connectivity in selected cases, using multi-modal neuroimaging. Skin biopsies are obtained on sequenced individuals and converted to fibroblasts. Several fibroblast lines have been reprogrammed into induced pluripotent stem cells for functional genomic studies (see ZIA-MH002810-15). Genome sequencing began in 2012 using technology that captured only the exome, or the expressed portions of the genome. Although no rare, damaging mutations were found that were shared by the majority of cases in our study, we did identify many promising variants shared by distantly-related cases. These variants were submitted to the Bipolar Sequencing Consortium where they have become part of a large meta-analysis that brings together samples from many groups around the world in order to improve statistical power to detect variants of modest effect. In collaboration with investigators at Regeneron, Inc., we have performed exome sequencing on 715 participants. We are now working on the data analyses. With this data set, we will be able to look for recurrent rare mutations, as well as mutations that have accumulated within individual genes and gene-sets. The current sample size is well powered to detect variants that confer substantial risk for BD. If such variants are not detected, larger samples will be needed to detect variants that confer more modest risk of illness. In collaboration with ISB, and the Bipolar Disorder Genome Study (BiGS), we have analyzed whole-genome sequences performed on 200 members of 41 families multiply affected with BD. Several classes of coding and non-coding (regulatory) variants segregating in these pedigrees were enriched for neuronal excitability genes. Ongoing work is aimed at confirming these findings in additional samples and characterizing the functional impact of the implicated genetic variants. If confirmed, these results could have important implications for our understanding of the causes of BD and provide clues for better treatment. In collaboration with investigators at the Univ Pennsylvania, Univ Miami, Case Western Reserve, and Univ Kansas, we have performed whole-genome sequencing on a larger set of individuals ascertained from Amish and Mennonite communities. The goal was to develop a population specific reference panel (the Anabaptist Genome Reference Panel or AGRP) that will allow us to infer rare genetic variants in individuals who have not undergone whole genome sequencing, thus increasing sample size at greatly reduced cost. Phase I of the AGRP was completed this year. While the data cannot be distributed, we have set up an imputation server so outside researchers working with Anabaptist populations can use the AGRP to impute their own samples. We have recently completed whole genome sequencing on another set of 60 Anabaptists. We will be incorporating this new data set with our existing data to further increase the imputation accuracy of rare variants. We are also searching for genetic markers that help predict response to lithium, one of the most effective treatments for BD. In collaboration with Univ Bonn, we did genome-wide genotyping on over 3000 cases. Confirmed biomarkers of lithium response would be an important step forward in the care of people with BD. We organized a large international collaboration, known as the Consortium on Lithium Genetics (ConLiGen), aimed at characterizing lithium response in large groups of patients using reliable instruments, followed by GWAS. Last year we found 4 markers in the same region on chromosome 21 that were associated with lithium response and supported by study in an independent sample. Over the past year, additional analyses in this dataset demonstrated that common genetic variants associated with schizophrenia predicted poorer response to lithium and, in joint analyses, implicated additional genetic loci harboring variants involved in both lithium response and schizophrenia risk. In the coming year, we will seek to replicate and extend these findings in additional large samples.